Robust and adaptive control system for regulation of arterial gas pressures by using transcutaneous sensors

Abstract

Robust and adaptive control schemes are investigated to regulate arterial oxygen pressure (PaCo2) and carbon dioxide pressure (PaCO2) independently at their desired levels by automatically adjusting two control inputs of the inspired oxygen concentration (FiO2) and the respiratory frequency (RF) in accordance with continuously monitored transcutaneous oxygen and carbon dioxide pressures (tcPO2 and tcPCO2). A linearized input-output model is given through the linearization at a steady-state level. The parameters and dead time in the linearized model are identified by using multiple models with a fixed dead time and adjustable parameters. In order to treat with individual differences and variations in the patient and the sensor dynamics and changes of the operating levels, the present control scheme consists of the adaptive control algorithm on a basis of the identified model and the robust controller with the Smith predictor to minimize the sensitivity to these variations. The effectiveness of the control scheme is investigated in animal experiments using mechanically ventilated dogs.

title = "Robust and adaptive control system for regulation of arterial gas pressures by using transcutaneous sensors",

abstract = "Robust and adaptive control schemes are investigated to regulate arterial oxygen pressure (PaCo2) and carbon dioxide pressure (PaCO2) independently at their desired levels by automatically adjusting two control inputs of the inspired oxygen concentration (FiO2) and the respiratory frequency (RF) in accordance with continuously monitored transcutaneous oxygen and carbon dioxide pressures (tcPO2 and tcPCO2). A linearized input-output model is given through the linearization at a steady-state level. The parameters and dead time in the linearized model are identified by using multiple models with a fixed dead time and adjustable parameters. In order to treat with individual differences and variations in the patient and the sensor dynamics and changes of the operating levels, the present control scheme consists of the adaptive control algorithm on a basis of the identified model and the robust controller with the Smith predictor to minimize the sensitivity to these variations. The effectiveness of the control scheme is investigated in animal experiments using mechanically ventilated dogs.",

T1 - Robust and adaptive control system for regulation of arterial gas pressures by using transcutaneous sensors

AU - Sano, A.

AU - Ohmori, H.

AU - Yazawa, M.

AU - Xue, J.

AU - Kikuchi, M.

PY - 1989/12/1

Y1 - 1989/12/1

N2 - Robust and adaptive control schemes are investigated to regulate arterial oxygen pressure (PaCo2) and carbon dioxide pressure (PaCO2) independently at their desired levels by automatically adjusting two control inputs of the inspired oxygen concentration (FiO2) and the respiratory frequency (RF) in accordance with continuously monitored transcutaneous oxygen and carbon dioxide pressures (tcPO2 and tcPCO2). A linearized input-output model is given through the linearization at a steady-state level. The parameters and dead time in the linearized model are identified by using multiple models with a fixed dead time and adjustable parameters. In order to treat with individual differences and variations in the patient and the sensor dynamics and changes of the operating levels, the present control scheme consists of the adaptive control algorithm on a basis of the identified model and the robust controller with the Smith predictor to minimize the sensitivity to these variations. The effectiveness of the control scheme is investigated in animal experiments using mechanically ventilated dogs.

AB - Robust and adaptive control schemes are investigated to regulate arterial oxygen pressure (PaCo2) and carbon dioxide pressure (PaCO2) independently at their desired levels by automatically adjusting two control inputs of the inspired oxygen concentration (FiO2) and the respiratory frequency (RF) in accordance with continuously monitored transcutaneous oxygen and carbon dioxide pressures (tcPO2 and tcPCO2). A linearized input-output model is given through the linearization at a steady-state level. The parameters and dead time in the linearized model are identified by using multiple models with a fixed dead time and adjustable parameters. In order to treat with individual differences and variations in the patient and the sensor dynamics and changes of the operating levels, the present control scheme consists of the adaptive control algorithm on a basis of the identified model and the robust controller with the Smith predictor to minimize the sensitivity to these variations. The effectiveness of the control scheme is investigated in animal experiments using mechanically ventilated dogs.